Blind Analysis of Standard Samples

Single-operator characteristics are determined by analyzing a sample whose concentration of analyte is known to the analyst. The second step in verifying a method is the blind analysis of standard samples where the analyte s concentration remains unknown to the analyst. The standard sample is analyzed several times, and the average concentration of the analyte is determined. This value should be within three, and preferably two standard deviations (as determined from the single-operator characteristics) of the analyte s known concentration. 

The analysis of a standard sample whose composition is unknown to the analyst. 

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It cannot be overemphasized that these values are for data from many laboratories in blind studies. They are useful for interpreting the results of analysis of unknown samples, as analyzed by a number of laboratories. They obviously do not correspond to the values for the repeatability (single laboratory) reported in the literature for standard solutions, recoveries of added analytes, and comparisons with other methods. Rather, the values in Figure 3 reflect the expected precision on real blind samples analyzed under somewhat ideal conditions. Analysis under practical conditions would be expected to be somewhat poorer analysis in a single laboratory by a single analyst would be expected to be considerably better. On balance, then. Figure 3 approximates what should be expected of methods operated at the indicated levels. 

Agency. A second example of an external method of quality assessment is the voluntary participation of the laboratory in a collaborative test (Chapter 14) sponsored by a professional organization such as the Association of Official Analytical Chemists. Finally, individuals contracting with a laboratory can perform their own external quality assessment by submitting blind duplicate samples and blind standard samples to the laboratory for analysis. If the results for the quality assessment samples are unacceptable, then there is good reason to consider the results suspect for other samples provided by the laboratory. 

The on-site version of AMDIS is a 16-bit Windows application running under OS2 operating system of the Dolch PC. This version of AMDIS was specially designed by NIST (National Institutes of Standards and Technology) for OPCW on-site analysis use. Its role in the postprocessing of analysis data is equivalent to the role of the blinded mode software in regard to the general control of the instrument and the acquisition of the data restrict the information on the identity of chemicals present in the sample to chemicals that are only relevant to the inspection aim. 

Standard Operating Procedure (SOP) SOP-LAB-EQP-005, Bruker EM640S Portable GC/MS with AMDIS Data Analysis Software (Blinded Mode) for Qualitative Analyses of Liquid Samples Prepared by On-site Methods, Version 3, The Technical Secretariat of the Organization for the Prohibition of Chemical Weapons, The Hague, 1999. 

There are several concepts and terms that are essential to discussions about QA, even the concept itself. While at a very detailed level any definition can be challenged as being too narrow or too broad, the definitions presented below are useful (20). It should be noted that these terms are quite recent in definition and are not usually given in statistics books. Other terms like pollution have evolved over hundreds of years (21). Some key terms used in the field like reproducibility, standard deviation, standard error, replicate analysis, blanks, spiked samples and blind samples are self-explanatory. 

Positive, blank, and interferent samples were prepared using standard MECHEM methods. All samples were marked by sampling personnel in a manner that made it impossible for analysts to determine the composition of the sample during analysis. Nomadics personnel and dog handlers were not given any information on sample identity until analysis of samples was completed and results were submitted for scoring (i.e., the tests were conducted in a blind fashion). 

An example of a control chart is illustrated in Figure 3.6, representing a plot of day-to-day results of the analysis of a pooled serum calcium or a control sample that is run randomly and blindly with samples each day. A useful inner control limit is two standard deviations since there is only 1 chance in 20 that an individual measurement will exceed this purely by chance. This might represent a warning limit. The outer limit might be 2.5 or 3cr, in which case there is only 1 chance in 100 or 1 chance in 500 a measurement will fall outside this range in the absence of systematic error. Usually, one control is run with each batch of samples (e.g., 20 samples), so several control points may be obtained each day. The mean of these may be plotted each day. The random scatter of this would be expected to be smaller by VA, compared to individual points. 

Work is underway to standardize the test method described here as a new ASTM standard. An Inter-Laboratory Study (ILS) is proposed to include at least nine each of gasoline and diesel Tier 2 class materials containing sulfur levels between <10 and 80 mg/kg in gasoline and between <10 and 80 mg/kg in diesels. Some blind National Institute of Standards and Technology (NIST) Standard Reference Materials (SRM) and solvent blanks are also plaimed for the cross check. The ILS will follow a protocol of an initial analysis of a set of samples and solvent blanks, and after an elapsed time of at least 12 h but no more than 72 h, a second set of measurements on the same set of samples and blanks will be completed. We expect this ILS to be completed by the end of2005. 

In order to improve the accuracy and precision of the measurement it is important that the known samples of analyte used for the calibration curve are made up in the same matrix as the real sanples, i.e. blank plasma, urine, etc. For quality control a series of samples undergoing analysis should also contain some standards of known concentration (-10%) and also some blind samples where the concentration is known but not by the operative carrying out the assay. 

RMS = root mean square noise of the instrument. SEC = standard error of calibration for each constituent. SEA = standard error of analysis or the difference between analysis values from the same samples analyzed by NIR and the reference laboratory. SED = standard error of a difference. Factory SED = standard error of the difference between the same samples analyzed by the master and slave instrument at different times. H = standardized H statistic. SEE = standard error of the laboratory reference values. (This statistic can be either the difference between duplicates in one laboratory or the difference between the same samples analyzed by two different laboratories.) M SEE = standard error of blind duplicates in the master reference laboratory. 

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